The aim of this study from Issue 15 of the Analytix Reporter was to develop a headspace solid phase microextraction (HS-SPME-GC-MS) method for high-throughput analysis and detection of early volatile biomarkers (prenol, prenal, isopentenol, hexanal, dimethyl disulfide, dimethyl trisulfide, 2-methylfuran, and 2-pentylfuran) in rice as previously used experimentally as biomarkers.
INTRODUCTION
Stored grains can be infested by a variety of pests that can cause brain damage and affect their quality and nutritional standards. Pest infestation in stored rice is responsible for postharvest losses of 9% in developed countries and even larger worldwide. Typical insect pest control methods that implement chemical insecticides have been gradually replaced by modern stored-product integrated pest management (IPM) programs that represent an eco-friendly and environmentally safe approach to pest control. IPM decision-making is based on knowledge of population dynamics and threshold insect density, where appropriate monitoring tools are of great importance. A variety of monitoring methods are employed. For instance, pheromone traps are typically used as a monitoring method in which adult insects are targeted. However, an adult female insect can produce hundreds of eggs before being detected, which could delay pest control actions. Thus, the use of new monitoring methods for early insect detection would be highly beneficial for fine-tuning and improving IPM programs.
In this article, solid-phase microextraction (SPME) is shown to be a viable alternative as a sample preparation method. Compared to other preconcentration techniques, SPME is simple, inexpensive, and solvent-free. It is fully automatable, and no thermal desorption unit or modifications to the GC instrument are necessary. Compatible with all GC systems, SPME can be used by practically every laboratory. The objective of this study was to use SPME with GC-MS analysis as a method to detect insect biomarkers as a tool for the identification of early insect infestation in stored grains, such as rice.
EXPERIMENTAL CONDITIONS
The HS-SPME method optimization was achieved using spiked rice samples obtained from a local market with undetectable GC-MS levels of studied analytes. During method development, fiber selectivity, extraction time (2, 5, 10, 15, 20 min), and temperature (30, 40, 50 and 60 °C) parameters were studied. For this purpose, 1 g of rice was spiked at 10 ng/g with 1 µL of a 10 µg/mL solution of analytes prepared in methanol. The HS-SPME-GC-MS method is summarized in Tables 1 and 2 within the full article.
RESULTS & DISCUSSION
A fiber selectivity study was performed using PDMS, DVB/PDMS, CAR/PDMS, and DVB/CAR/PDMS SPME fibers to evaluate the performance and effectiveness of each fiber coating chemistry on the headspace extraction of insect volatile biomarkers in a 10 ng/g spiked rice sample.
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CONCLUSION
The HS-SPME-GC-MS method can be used in integrated pest management (IPM) programs as a fast and versatile monitoring approach/tool for the identification of early insect infestation in store grains such as rice.
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